Chronobiology International, Early Online: 1–13, (2014) ! Informa Healthcare USA, Inc. ISSN: 0742-0528 print / 1525-6073 online DOI: 10.3109/07420528.2014.957305

ORIGINAL ARTICLE

Investigation of the effectiveness of a split sleep schedule in sustaining sleep and maintaining performance Melinda L. Jackson1, Siobhan Banks2, and Gregory Belenky3 Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia, 2Centre for Sleep Research, University of South Australia, Adelaide, Australia, and 3Sleep and Performance Research Center, Washington State University, Spokane, WA, USA

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

1

Shift work is common in today’s society, and is associated with negative health outcomes, and accidents and incidents. These detrimental effects can be primarily attributed to sleeping and working at an adverse circadian time. The aim of this study was to examine whether a split sleep schedule is as effective as a consolidated day shift or night shift schedule for maintaining performance and sustaining sleep. Fifty-three healthy male volunteers (mean ± SD age ¼ 26.51 ± 4.07 years) underwent a randomized three condition study design. A split sleep condition involving two 5-h sleeping opportunities in 24 h [time in bed (TIB) 0300 h–0800 h and 1500 h–2000 h] was compared to a 10-h consolidated nighttime sleep (TIB 2200 h–0800 h) and 10-h consolidated daytime sleep (TIB 1000 h–2000 h). All participants underwent a baseline period of 10 h of nocturnal time in bed (TIB) followed by a 5-d simulated workweek spent in one of the three conditions. Polysomnography, psychomotor vigilance task, digit-symbol substitution task and subjective state were assessed. During the 5-d simulated workweek, participants in the nighttime sleep condition slept the most (total sleep time per day (TST) 8.4 h ± 13.4 min), followed by the split sleep condition (TST 7.16 h ± 14.2 min) and the daytime sleep condition (TST 6.4 h ± 15.3 min). Subjective sleepiness was highest in the daytime sleep condition and lowest in the nighttime sleep condition. No significant differences in performance were observed between the conditions. Compared to a nighttime consolidated sleep opportunity or split sleep, placement of a consolidated sleep opportunity during the day yielded truncated sleep and increased sleepiness. Further research in real-world situations is warranted to fully assess the efficacy of alternative split sleep schedules for improving safety and productivity. Keywords: Fatigue risk management, scheduling, shift work, sleepiness, split sleep, vigilance

INTRODUCTION

opportunity, are typically only able to obtain about 5 h of daytime sleep before their sleep is truncated by the combination of decreasing homeostatic drive for sleep and increasing circadian drive for wake (Goel et al., 2011; Van Dongen et al., 2010). This leads to cumulative sleep restriction over extended periods of time. Studies of restricted sleep show that over days of sleep restriction there is a cumulative sleep dose-dependent degradation in alertness and performance, which can occur even during mild sleep restriction (loss of 51 h of sleep/ night); and that 7–8 h of consolidated nocturnal sleep in 24 h appear to sustain performance over multiple days, if not indefinitely (Belenky et al., 2003; Van Dongen et al., 2003). When the main sleep period is restricted or absent, adding supplementary naps improves alertness and performance (Bonnet, 1991; Dinges et al., 1987;

Shift work and extended work hours are associated with daytime sleepiness and insomnia, and reduced alertness, work productivity and quality of life (Rajaratnam & Arnedt, 2001). Shift work has also been linked to negative health effects, including increased cardiovascular morbidity and mortality, and increased accident risk (Drake & Wright, 2011; Rajaratnam & Arnedt, 2001; Wehrens et al., 2012). One key problem for shift workers, from which many of these negative consequences stem, is reduced sleep. The extensive literature on shift work indicates that, for the same duration of consolidated sleep opportunity, actual sleep obtained is critically dependent on the placement of the sleep opportunity ˚ kerstedt, 2003; with respect to the circadian phase (A Drake & Wright, 2011). Shift workers coming off duty in the morning, with an 8–10 h consolidated sleep

Submitted February 11, 2014, Returned for revision July 27, 2014, Accepted July 30, 2014

Correspondence: Melinda L. Jackson, Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne 3010, Australia. Tel: 613 9035 6129. Fax: 613 9347 6618. E-mail: [email protected]

1

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

2

M. L. Jackson et al.

Ficca et al., 2010; Sallinen et al., 1998; Takeyama et al., 2005). The term ‘‘split sleep’’ means two or more sleep opportunities in a 24-h period, ranging from a main sleep and a supplemental nap (e.g. 6 and 2 h), through a main sleep and several naps, to multiple naps with no clear main sleep (Belenky et al., 2008, 2011; Bonnet & Arand, 2003; Takeyama et al., 2005). Spilt sleep schedules are common practice in a number of industries including healthcare, maritime and transport. Split sleep may restore alertness and performance as effectively as consolidated sleep (Nicholson et al., 1985; Schweitzer et al., 2006). Laboratory evidence to date suggests that when the longer sleep period is placed at night, split sleep is similar to consolidated sleep in both duration and recuperative value, and that the critical factor in sustaining performance is total sleep time in 24 h (Belenky et al., 2008). For example, physicians working day shifts and sleeping at night, versus working night shifts and having their main sleep during the day supplemented by on-shift nighttime naps, are able to accumulate approximately 7 h of total sleep time over 24 h and perform equally well on the psychomotor vigilance task (PVT) in both conditions (McDonald et al., 2013). Total sleep time is strongly influenced by the time of day that the sleep opportunity occurs. A laboratory study of maritime workers found that sleep opportunities that were placed during the day (e.g. 12:00 h– 18:00 h and 18:00 h–24:00 h) had, on average, 1–1.5 h less total sleep time compared to sleep periods placed during the night (Eriksen et al., 2006). While studies support the idea of flexibility in splitting sleep for maintaining performance (Folkard & Tucker, 2003; Horne & Reyner, 1999; Jones et al., 2006), many have failed to take into account whether the placement of the split sleep opportunity was at an adverse circadian time (e.g. the longer sleep was placed at night (nocturnal anchor sleep) and the shorter sleep during the day). It is therefore unclear whether split sleep per se degrades performance. Further to this, it is important to also compare the effect of a split sleep opportunity to the same total duration of sleep opportunity consolidated at night and during the day. The current study aims to overcome these shortcomings by examining split sleep opportunities placed during a period of high sleep propensity, and by comparing split sleep to both a consolidated daytime and nighttime sleep opportunity. Data on the effectiveness of a split sleep schedule will have particular relevance for occupational environments in determining the adequate duration and effective placement of the sleep opportunities. The aim of this study was to compare a sleep split schedule, where the sleep opportunities are split evenly into two sleep periods, to two conditions in which sleep was consolidated into a single period (either daytime consolidated sleep and or nighttime consolidated sleep), to determine the effects of those sleep patterns on sleep, performance and subjective state.

MATERIALS AND METHODS Participant recruitment and screening Participants were recruited from the general population of healthy young men ranging in age from 22 to 40 years. Blood samples were collected during the study to assess metabolic measures (data not shown), therefore women and obese men (BMI430) were excluded from the study, as were participants whom would have difficulty with intravenous (IV) catheters. Prospective participants responded to advertisements in local newspapers and on the internet and underwent an initial telephone screening interview. They then attended two laboratorybased screening sessions beginning with an informed consent procedure, and included a physical exam, blood and urine samples and a variety of questionnaires to assess suitability for participation. Participants were required to meet the following additional criteria to be eligible for participation in the study: psychologically and physically healthy, as assessed by the study physician and medical history; no clinically significant abnormalities in blood and urine and free of traces of drugs; free of traces of alcohol by breathalyzer; no history of drug or alcohol abuse in the past year and no history of methamphetamine abuse; not a current smoker (by questionnaire); no history of a learning disability or brain injury (by questionnaire); no previous adverse reaction to sleep deprivation (by history and questionnaire); not vision impaired unless corrected to normal; no sleep or circadian disorder; good habitual sleep, between 6 and 10 h in duration, verified by wrist actigraphy and diary in the week before the study; regular bedtimes, habitually getting up between 0600 h and 0900 h; neither extreme morning- nor extreme evening-type (by questionnaire); no travel across timezones or shift work within one month of entering the study; native English speaker. This study was approved by the Washington State University Institutional Review Board (IRB) and all participants gave written informed consent. The experimental protocol conformed to international ethical standards (Portaluppi et al., 2010). Design A three-condition design was developed – one experimental condition (split sleep opportunity) and two control conditions (consolidated nighttime sleep opportunity and consolidated daytime sleep opportunity). All three conditions were continued for a simulated workweek of 5 consecutive days. Participants in the split sleep and consolidated nighttime sleep conditions arrived in the laboratory at 0900 h on Day 1 and completed data collection for the present study at 1400 h on Day 10. Participants in the daytime sleep condition were part of a separate study that involved two 5-d work periods, and lived in the same laboratory as participants in the current study for 16-d (Van Dongen et al., 2011); only data from the first 5-d work week from that study, including baseline and recovery, was used in Chronobiology International

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

Efficacy of split sleep schedule on sleep and performance this study. The same exclusion criteria were applied to participants in both studies. The study began with two baseline days with nighttime sleep, followed by a 5-d simulated workweek in one of the three sleep opportunity conditions, and ended with two recovery days, again with nighttime sleep (Figure 1). The design held constant at 10 h the total daily amount of time available for sleep for all three conditions – split sleep opportunity (0300 h–0800 h and 1500 h–2000 h), consolidated nighttime sleep opportunity (2200 h–0800h) and consolidated daytime sleep opportunity (1000 h–2000 h). Thus, all three conditions had the same 90-h total sleep opportunity (10 h per day) across the 10-d study. A 10-h sleep opportunity was provided in all conditions to allow participants to obtain sufficient sleep throughout the study and to approximate a 14-h on duty/10-h off duty schedule (Banks et al., 2010; Van Dongen et al., 2011). While this amount of sleep would not typically occur in the real world, this laboratory-based study allowed us to determine the effect of different sleep schedules independent of sleep restriction imposed by the study protocol. The split sleep experimental condition was implemented as two, 5-h daily sleep opportunities; one from 0300 h to 0800 h and the other from 1500 h to 2000 h. This placed the sleep opportunity in the first instance at a time when sleep propensity is high and in the second instance at a time when sleep propensity, at least later in the interval, is low. The consolidated nighttime control sleep condition was implemented as a 10-h daily nighttime sleep opportunity from 2200 h to 0800 h. This placed the sleep opportunity at times when it is likely that homeostatic drive for sleep was high and the circadian drive for wakefulness was low, promoting sustained, consolidated sleep (Dijk & Czeisler, 1994). Such a consolidated nighttime sleep opportunity would be typically associated with day shift work. The consolidated daytime control sleep condition was implemented as a 10-h daytime sleep opportunity from 1000 h to 2000 h. This placed the sleep opportunity initially at a time when sleep propensity is high due to high homeostatic drive and subsequently at a time when sleep propensity is generally low due to the increasing circadian drive for wakefulness. In addition, transition naps were implemented for both split sleep and daytime sleep conditions to aid in the transition to the workweek schedule at the beginning of the 5-d work week, and to aid the switch back to nighttime sleep at the end of the workweek (Figure 1). During their days in-residence at the Sleep and Performance Research Center, participants had no contact with the outside world. They slept, ate and completed performance tests within the confines of the sleep laboratory. There was no cell phone contact, no email, no visitors and no live television, radio or internet. During scheduled sleep periods, bedroom lights were turned off and participants were not permitted to engage in any activities other than sleeping !

Informa Healthcare USA, Inc.

3

or resting. Ambient temperature throughout the laboratory was kept at 72 ± 2 F, and lighting levels were fixed at 50 lux during scheduled wakefulness. Participants were served 3 calorie-controlled meals per day at fixed intervals.

Measures To assess effects of schedule on sleep and performance, measurements of sleep, performance and subjective state were made (Figure 1). During off-duty days, performance testing was significantly reduced to mimic rest days in the real world. Performance testing practice occurred on Day 1; these practice sessions were not used for analysis. Sleep During most scheduled sleep periods, PSG was recorded using digital equipment (Nihon Kohden, Foothill Ranch, CA). Electroencephalography (EEG) was recorded from frontal (F3, F4), central (C3, C4) and occipital (O1, O2) locations, referenced against the mastoids (M1, M2). Electrooculography (EOG), electromyography (EMG) and electrocardiography (ECG) were also recorded. Sleep stages were scored using standard technical specifications and rules recommended by the American Academy of Sleep Medicine (AASM; Iber & Ancoli-Israel, 2007). The following PSG/Sleep variables were compared between conditions, time in bed, total sleep time, N3 sleep time, REM sleep time, N2 sleep time, N1 sleep time, sleep latency, latency to N3 sleep, latency to REM sleep. The sleep periods that were recorded and the comparisons made across conditions are shown in Figure 1. Every third or fourth day, electrodes were removed to give participants an opportunity to take a shower and to heal any skin irritation caused by the electrodes. Performance and subjective assessments The PVT is a standard assay of vigilance used to assess fatigue, and was used as the primary outcome measure in the current study (Dorrian et al., 2005). The number of performance lapses (reaction times greater than 500 ms) was extracted. The PVT has high sensitivity to fatigue and favorable statistical properties (Lim & Dinges, 2008). A 10-min PVT was administered alone or in combination with the subjective state measures for the three conditions. For all conditions across the workweek, eight PVT sessions were performed in every 24-h period. Secondary performance outcomes were derived from a computerized neurobehavioral test battery, administered either alone or in combination with a PVT. The battery consisted of the computerized versions of the Digit Symbol Substitution test (DSST), the Karolinska ˚ kerstedt & Gillberg, 1990); a Sleepiness Scale (KSS; A visual analog scale of mood, from elated to depressed (VAS-M; Van Dongen et al., 2004); and the Positive Affect Negative Affect Schedule (PANAS; Watson et al., 1988), which is a measure of positive and negative emotion.

M. L. Jackson et al.

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

4

FIGURE 1. PSG recording, Psychomotor Vigilance Test (***), Neurobehavioral Test Battery (X) schedule for the consolidated nighttime sleep (top panel), split sleep (middle panel) and consolidated daytime sleep (bottom panel) conditions. Baseline periods included PSG A and B for all conditions. For the nighttime and daytime sleep conditions, the work week sleep periods included PSG D and E, and for the split sleep condition the work period included PSG E, F, G and H. The recovery sleep periods included PSG F and G for the nighttime sleep condition, PSG I and J for the split sleep condition, and PSG G and H for the daytime sleep condition.

Chronobiology International

Efficacy of split sleep schedule on sleep and performance

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

For each, an overall score was extracted, except for the PANAS, for which both positive and negative affect scores were determined. The DSST is a performance test involving matching numbers to symbols (Wechsler, 1997). The computer screen showed a key with a set of nine symbols, each with a corresponding digit (1–9). When given a symbol in another, fixed location on the screen, participants were required to type its corresponding number. After the response, a new symbol was immediately presented. The number of correct responses in the 3-min task duration was extracted, yielding a measure of cognitive throughput. The DSST is sensitive to acute total sleep deprivation and chronic sleep restriction (Van Dongen et al., 2003).

Statistical analysis The primary statistical design involved a mixed model analysis of variance (ANOVA) comparison of the withinsubject effects of condition (split sleep, nighttime sleep and daytime sleep) on the between-subjects factors of PSG variables, performance (PVT lapses and DSST) and subjective measures (KSS, PANAS and VAS-M). For the PSG variables, the secondary statistical analyses involved a comparison of within-subjects effects of condition by sleep period (baseline sleep period 1 [BL1], baseline sleep period 2 [BL2], work period 1 [W1], work period 2 [W2], recovery [R]) mixed model ANOVAs. PSGs A and B were used in the analysis to compare baseline sleep across conditions (Figure 1). PSGs C and D for the nighttime and daytime sleep conditions, and PSGs E, F, G and H in the split sleep condition were used in the analysis comparing sleep during the work week across conditions. For the analysis comparing recovery sleep across conditions included only one equivalent PSG in each condition; PSG G for the nighttime sleep condition, PSG J for the split sleep condition and PSG H for the daytime sleep condition (Figure 1). A sub analysis of the six PSG-recorded napping opportunities in the split sleep condition was also examined using a mixed model approach, comparing a within-subject factor (nap type: afternoon nap, morning nap), with post-hoc t-tests. In order to determine whether performance and subjective measures changed across work days and within work days between groups, secondary statistical analyses involved condition by workday (Workday 1–5), and condition by time of day (Session 1–8 for PVT and Session 1–4 for all other measures), mixed model ANOVAs. Planned group comparisons were performed for all analyses. RESULTS Participants Fifty-three male participants completed the study (mean ± SD age ¼ 26.51 ± 4.07 years). Nineteen participants were randomized to the consolidated nighttime sleep condition, 17 were randomized to the split sleep condition, and 17 were randomized to the consolidated !

Informa Healthcare USA, Inc.

5

TABLE 1. Demographic details of the participants in the consolidated nighttime sleep, split sleep and consolidation daytime sleep conditions.

Age (years) BMI MEQ ESS PQSI

Nighttime sleep

Split sleep

Daytime sleep

25.8 24.4 36.8 4.2 2.2

26.3 23.9 38.4 3.6 2.3

27.5 24.8 36.9 4.6 2.5

BMI, body mass index; MEQ, morningness–eveningness questionnaire; ESS, Epworth Sleepiness Scale; PQSI, Pittsburgh Sleep Quality Index.

daytime sleep condition. One participant in the nighttime sleep condition was excluded from the sleep and performance analysis due to a suspected sleep disorder, leaving 18 participants in the consolidated nighttime sleep condition. There was no significant difference in age of the participants across the conditions (F2,48 ¼ 0.74; p ¼ 0.48). Table 1 displays the demographic information of participants in each group.

Sleep Two participants in the daytime sleep condition were excluded from the sleep analysis – one due to poor sleep efficiency throughout the study (due to flu-like symptoms) and another due to light exposure during the sleep periods. This left 15 participants in the daytime sleep condition, 18 participants in the nighttime sleep condition and 17 participants in the split sleep condition for the PSG analysis. The PSG-recorded sleep periods for the three sleep conditions – nighttime sleep, the split sleep and the daytime sleep for baseline (two recordings; BL1, BL2), work period (2 recordings; W1, W2) and recovery (one recording; R) – were compared. By design, time in bed (TIB) was equivalent for the three conditions across the baseline, work and recovery periods. For the PSG recordings, total TIB was 20 h for the two baseline recordings, 20 h for the two work period recordings and 10 h for the single recovery recording. The main effect of condition was significant for minutes of total sleep time (TST) (F2,204 ¼ 12.49, p50.001). Participants in the nighttime sleep condition obtained significantly more sleep and participants in the daytime and split sleep conditions, and participants the split sleep condition obtained significantly more sleep than participants in the daytime sleep condition (p50.05; Figure 2A). There was a significant interaction between condition and sleep period for TST (F8,192 ¼ 5.92, p50.001). During the work period, the nighttime sleep condition obtained significantly more TST than participants in the split and daytime sleep conditions (ps50.05). During recovery, participants in split sleep condition obtained more TST than participants in daytime sleep condition (p50.05). There was

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

6

M. L. Jackson et al.

FIGURE 2. Polysomnographic measures across two baseline sleep periods (BL1, BL2), two sleep periods during the work week (W1, W2), and one recovery sleep period (R) for the nighttime sleep (black circles), split sleep (grey squares) and daytime sleep (white triangles) conditions. Panel A depicts total sleep time (TST), panel B depicts stage N2 sleep, panel C depicts REM sleep and panel D depicts sleep onset latency in minutes across the five sleep periods. Error bars represent standard errors.

also a main effect of sleep period (F4,192 ¼ 21.07, p50.001). Participants obtained more sleep during the baseline period compared to the work period and recovery (p50.05). For minutes of stage N2 sleep there were no significant differences between conditions (F2,204 ¼ 1.11, p ¼ 0.33; Figure 2B). There was a significant interaction between sleep period and condition for stage N2 sleep (F8,192 ¼ 6.10, p50.001). During the work period, participants in the daytime sleep condition obtained less N2 sleep than participants in the nighttime sleep condition. There was a significant main effect of sleep period (F4,192 ¼ 22.97, p50.01), with the most N2 sleep obtained during baseline period and the least obtained during the work period. Overall, REM sleep differed significantly between all three conditions (F2,204 ¼ 16.52, p50.001; Figure

2C). Participants in the split sleep condition obtained significantly more REM sleep than the daytime sleep condition, however, still obtained significantly less than the nighttime sleep condition, despite having equal amounts of baseline time in bed. There was a significant interaction between condition and sleep period for REM sleep (F8,192 ¼ 5.08, p50.001). During the work period, participants in the nighttime sleep condition obtained more REM sleep than the split and daytime sleep conditions. There was also a significant main effect of sleep period (F4,192 ¼ 3.67, p50.01). For sleep onset latency (SOL; in minutes), there were no significant differences across the conditions (F2,192 ¼ 1.94, p ¼ 0.15; Figure 2D). There was a significant interaction between sleep period and condition for SOL (F8,192 ¼ 4.75, p50.001). During the work period, participants in the nighttime sleep condition had Chronobiology International

Efficacy of split sleep schedule on sleep and performance

7

the morning naps having more N2 sleep than the afternoon naps (123.4 ± 4.2 min versus 78.4 ± 5.4 min). There was no difference in sleep latency between the nap periods (p ¼ 0.48).

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

FIGURE 3. Average total sleep time in minutes during the afternoon naps (1500 h–2000 h; grey bars) and morning naps (0300 h– 0800 h; black bars) in the split sleep condition. Error bars represent standard errors.

shorter SOL than participants in the daytime sleep condition. There was a significant main effect of sleep period (F4,192 ¼ 3.23, p50.05). For latency to stage N3 sleep, there were no significant differences between conditions (F2,48 ¼ 1.57, p ¼ 0.22), however there was a significant interaction between sleep period and condition (F8,192 ¼ 3.70, p50.001; Figure 2E). During the work period, participants in the split sleep condition displayed significantly longer latency to stage N3 than participants in the nighttime sleep condition. During the recovery period, participants in the daytime sleep condition displayed longer latency to stage N3 than participants in the nighttime and split sleep conditions. There was also a significant main effect of sleep period (F4,192 ¼ 3.58, p50.01). For latency to REM sleep, stage N1 sleep or stage N3 sleep, there were no significant differences between conditions, or were there any interactions between condition and sleep period (all p40.05).

Sleep in the split sleep condition A sub-analysis was performed on the split sleep condition data, comparing the afternoon naps and morning naps. There was a significant main effect of nap type for TST (Figure 3; F5,80 ¼ 29.94; p50.001). TST was significantly longer in the morning nap opportunities (M ¼ 260.2 ± 7.56 min) than in the afternoon nap opportunities (M ¼ 154.3 ± 6.63 min; ps50.001). There was significantly more N3 in the morning naps compared to the afternoon naps (58.1 ± 4.3 min versus 33.3 ± 3.3 min; F5,80 ¼ 7.66; p50.001). Similarly, more REM sleep was observed in the morning naps compared to the afternoon naps (69.7 ± 3.1 min versus 34.2 ± 3.0 min; F5,80 ¼ 19.39; p50.001). Stage N1 sleep differed significantly between the nap periods (F5,80 ¼ 4.09; p50.01). The first morning nap and the last afternoon nap had less stage N1 sleep than the other nap periods. Stage N2 sleep also differed significantly between the nap periods (F5,80 ¼ 4.09; p50.01), with !

Informa Healthcare USA, Inc.

Performance Psychomotor vigilance task The primary performance outcome measures for the study were the number of lapses (RTs4500 ms) and fastest 10% of RTs on the PVT. Performance data from the two participants who were excluded from the sleep analyses was examined and compared to the mean PVT performance of the participants who were included in the sleep analysis, and they did not significantly differ. Therefore, the performance data for these participants was included in the analyses. Two participants in the nighttime sleep condition and two participants in the split sleep condition were excluded from the PVT analysis as they were found to be noncompliant on this task. These participants exhibited an overall average of 8.82 (SD 4.87) lapses on the PVT, whereas the other participants had an overall average of only 1.99 (SD 1.56). This level of PVT performance is worse than that reported in severely sleep restricted participants (Belenky et al., 2003). This left 17 participants in the daytime sleep condition, 16 participants in the nighttime sleep condition and 15 in the split sleep condition for the PVT analysis. The primary statistical analysis of the effect of condition was not statistically significant for PVT lapses (F2,1677 ¼ 0.94, p ¼ 0.39). In order to examine changes in performance over days within each condition, a further analysis of PVT lapses investigated the interaction of condition by work day (Figure 4A). This two-way interaction was not significant (F8,1665 ¼ 0.95, p ¼ 0.47), but the main effect of work day was statistically significant (F4,1665 ¼ 4.72, p ¼ 0.001). A secondary analysis of PVT lapses investigated the interaction of condition by session (time of day), (collapsed over days). The two-way interaction was statistically significant (F14,1656 ¼ 6.90, p50.001; Figure 5A). In sessions 1 and 2, participants in the daytime sleep condition had significantly fewer lapses compared to the nighttime sleep condition (post-hoc ps50.05). In session 3, participants in the daytime sleep condition had significantly fewer lapses compared to the split sleep condition (p50.05). In sessions 4 and 5, participants in the split sleep condition had more lapses than the other conditions (ps50.05). In session 6, participants in the split sleep condition had more lapses than participants in the daytime sleep condition (p50.05). In session 7, participants in the split sleep condition had more lapses than the nighttime sleep condition (p50.05). In session 8, participants in the nighttime sleep condition had more lapses than the daytime sleep condition (p50.05). The main effect of session was also significant, with lapses increasing across the work shift (F7,1656 ¼ 16.40, p50.001).

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

8

M. L. Jackson et al.

FIGURE 4. Lapses (Panel A) and fastest 10% of reaction times (Panel B) on the 10-min Psychomotor Vigilance Test (PVT), Karolinska Sleepiness Scale (KSS) score (Panel C) and Visual Analogue Mood rating scale (Panal D) as a function of days at baseline and in the 5-d work period in the nighttime sleep (black circles), split sleep (grey squares) and daytime sleep (white triangles) conditions. Error bars represent standard errors.

The effect of condition for PVT fastest 10% of RTs was not statistically significant (F2,1677 ¼ 0.90, p ¼ 0.41), or was the two-way interaction of condition by work day, collapsed over session, was not significant (F8,1665 ¼ 1.41, p ¼ 0.34). However, the main effect of work day was statistically significant (F4,1665 ¼ 2.45, p ¼ 0.04), with a slight increase in RTs towards the end of the work week (Figure 4B). Secondary analysis of interaction of condition by session, collapsed over days for PVT fastest 10% of RTs revealed a significant interaction (F14,1656 ¼ 5.50, p50.001; Figure 5B). The main effect of session was also statistically significant (F7,1656 ¼ 7.24, p50.001).

Digit-symbol substitution test For the number of correct responses on the DSST, the effect of condition was not statistically significant (F2,968 ¼ 1.93, p ¼ 0.15), nor was the interaction between condition and work day (F8,956 ¼ 1.34, p ¼ 0.22). However, there was significant main effect of work day (F4,956 ¼ 22.66, p50.001), indicative of the known learning effect that occurs on this task. Analyses of condition by session showed a significant interaction (F6,959 ¼ 4.87, p50.001; Figure 5C). Participants in the

nighttime sleep condition had significantly higher DSST performance than participants in the split and daytime sleep conditions in sessions 3 and 4 (p’s50.05).

Subjective measures Karolinska sleepiness scale For the KSS, the primary analysis focusing on the main effect of condition yielded a significant effect (F2,968 ¼ 5.50, p ¼ 0.004). The two-way interaction of condition by work day was also statistically significant, with participants in the daytime sleep condition reporting significantly greater sleepiness on work days 1–4 (F8,956 ¼ 3.11, p ¼ 0.002; Figure 4C). There was no significant main effect of work day for KSS scores (p ¼ 0.74). The analysis of the interaction of condition by session was statistically significant (F6,959 ¼ 22.60, p50.001; Figure 5D). Daytime sleep participants reported higher levels of sleepiness towards the end of their work shift relative to the other two conditions. There was also a main effect of session for KSS scores (F3,959 ¼ 25.78, p50.001). Mood rating scales For the VAS-M, the primary analysis focusing on the effect of condition yielded a trend to significance Chronobiology International

Efficacy of split sleep schedule on sleep and performance

9

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

(F2,48 ¼ 2.83, p ¼ 0.07), as did the two-way interaction of condition by work day (F8,957 ¼ 1.77, p ¼ 0.08; Figure 4D). Participants in the split sleep condition rated their mood lower than the other two conditions across all work days (ps50.05). The main effect of work day was not significant (F4,957 ¼ 1.79, p ¼ 0.13). In order to investigate subjective mood as a function of session, a further analysis of the VAS-M examined the interaction of condition by session. The two-way interaction was not significant (F2,960 ¼ 1.69, p ¼ 0.12). There was, however, a significant main effect of session (F3,960 ¼ 4.92, p ¼ 0.002). For the positive affect scale of the PANAS, the primary analysis focusing on the main effect of condition yielded non-significance (F2,48 ¼ 2.09, p ¼ 0.13). Interactions of condition by work day trended towards significance (F8,956 ¼ 1.86, p ¼ 0.06), with a significant main effect of work day emerging (F4,956 ¼ 5.45, p50.001). Examination of PANAS positive affect as a function of session showed a significant interaction of condition by session (F6,959 ¼ 4.34, p50.001). Across most of the sessions within each work day, participants in the split sleep condition had significantly lower positive affect scores than participants in the nighttime and daytime sleep conditions (ps50.05). There was also a significant main effect of session (F3,959 ¼ 12.73, p50.001), with positive affect scores decreasing significantly across the work period (ps50.05). For the negative effect scale of the PANAS, the primary analysis focusing on the main effect of condition yielded non-significance (F2,968 ¼ 0.87, p ¼ 0.42). The interaction between condition and work day was not significant (F6,956 ¼ 0.81, p ¼ 0.59), however there was a significant main effect of work day (F4,956 ¼ 2.67, p ¼ 0.03). There was no significant interaction of condition by session (F6,959 ¼ 0.92, p ¼ 0.48), nor was there was a significant main effect session (F3,959 ¼ 1.31, p ¼ 0.27) for negative affect scores.

DISCUSSION

FIGURE 5. Lapses on the Psychomotor Vigilance Test (PVT; Panel A), PVT fastest 10% of reaction times (Panel B), Digit Symbol Substitution Test (DSST) correct responses (Panel C) and Karolinska Sleepiness Scale (KSS) scores (Panel D) at each test session per work day, collapsed over the 5-d work period for the nighttime sleep (black circles), split sleep (grey squares) and daytime sleep (white triangles) conditions. Error bars indicate standard error. Note that sessions were conducted at different times of day within each condition. For the PVT, the nighttime sleep condition testing was at 0900, 0930, 1200, 1230, 1500, 1530, 1800 and 1830; split sleep condition testing was at 2100, 2130, 0000, 0030, 0900, 0930, 1200 and 1230, and the daytime sleep condition testing was at 2100, 2130, 0000, 0030, 0300, 0330, 0600 and 0630. For KSS and DSST, the nighttime sleep condition testing was at 0900, 1200, 1500 and 1800, the split sleep condition testing was at 2100, 0000, 0900 and 1200, and the daytime sleep condition, testing was at 2100, 0000, 0300 and 0600. !

Informa Healthcare USA, Inc.

This study examined whether a split sleep schedule was as effective as a consolidated period of sleep, placed either during the day or during the night, for maintaining sleep and performance across a simulated week of work. Overall, participants in the nighttime and split sleep conditions obtained significantly more total sleep time than participants in the daytime sleep condition. While there was no clear effect of sleep schedule on performance measures, participants in the daytime sleep condition reported higher levels of sleepiness both within the work shift and across the simulated working week compared to the other two conditions, with no difference between the split and nighttime sleep conditions. Results of the present laboratory study suggest that split sleep schedules may be a good alternative to a consolidated daytime sleep in industries that allow for this kind of flexibility in their scheduling.

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

10

M. L. Jackson et al.

Despite the daily sleep opportunity of 10 h, TST, a determinant of recuperation (Banks et al., 2010; Wesensten et al., 1999), differed across the three conditions in a manner consistent with our knowledge of the human circadian rhythm in sleep propensity, and what is observed in shift workers in the real world ˚ kerstedt, 2003; Goel et al., 2011). In a healthy person (A with a consolidated 8 h sleep opportunity at a circadian phase with high sleep propensity, the normal sleep latency is typically between 10 and 12 min. For a consolidated sleep opportunity, the sleep latency reflects only a small shortening of actual sleep relative to sleep opportunity. With sleep split into two or more bouts, one goes through the process of falling asleep at least two times. As such, a split sleep opportunity could degrade alertness and performance only in so far as it might reduce TST in comparison to a consolidated sleep opportunity (Wesensten et al., 1999). TST in the nighttime and split sleep conditions in the current study were in the normal range of 7–9 h, compared to TST in the daytime sleep condition, which was in the mildly sleeprestricted range of 6–7 h. Similarly, REM sleep was reduced in the daytime sleep condition, with no effect on N3 sleep, consistent with previous field studies in shift worker populations (Foret & Benoit, 1974). REM sleep appears to be influenced by the circadian timing of the sleep period, which varied by condition, whereas N3 sleep, influenced by the homeostatic drive accumulated from prior wakefulness, was equivalent across conditions, as has been found in previous forced desynchrony studies (Paech et al., 2012). Importantly for recovery following shift work, the split sleep condition achieved more TST on the recovery night compared to the daytime sleep condition. This suggests that participants in the daytime sleep condition experienced more circadian adaptation, and thus found it difficult to obtain adequate sleep when attempting to switch back to a nighttime sleep schedule, which was not observed following a 5-d split sleep schedule. Our primary performance measure, PVT lapses, did not differ between the split sleep conditions and the two control sleep conditions, and PVT lapses were overall relatively infrequent across work days. The split sleep group did exhibit a higher number of lapses towards the end of their night work period and at the start of their morning work period. However, their performance plateaued relative to the daytime sleep group, whom exhibited increasing impairment across the work shift. Note that the sleep opportunity was 10 h per day for all days in all conditions. Thus, even for the participants in the daytime sleep condition (who had slightly restricted sleep), performance did not degrade significantly. In a study with a similar degree of mild daily sleep restriction over 7 d, only a small increase in PVT lapses was seen (Belenky et al., 2003). In addition, the experimental manipulation lasted 5 d in the current study; perhaps not sufficient to increase PVT lapses. For the DSST, there was evidence of improvement in performance

across all conditions over the course of the study, representing the well-known practice effects of this task (Van Dongen et al., 2003). Note these results must be taken with caution, as by design, the nighttime sleep condition had an extra DSST session prior to their working week, and therefore had additional practice on the task relative to the other conditions. Thus, performance was relatively unaffected by the split sleep schedule relative to the two other sleep conditions of what was an extended sleep opportunity, despite the clear circadian effects on actual sleep. However, if the sleep opportunity was restricted in the daytime sleep or split sleep conditions, as occurs more frequently in the real world, these results could be very different. Night shift workers typically obtain between 5–6 h of sleep between shifts (Foret & Benoit, 1974); 1–2 h less than the participants in the current study. Whether adequate sleep would be obtained under a split sleep schedule in the real world is unknown, and if not, performance may deteriorate to a greater extent than that observed in the current study. Subjective sleepiness on the KSS differed significantly among the three conditions, with participants in the daytime sleep condition reporting significantly more sleepiness than participants in the nighttime or split sleep conditions. As has been documented previously (Santhi et al., 2007), there appeared to be a ‘‘first-night effect’’ in the daytime sleep condition, with KSS scores highest on the first work day. Subjective sleepiness was also increased towards the end of the shift in the daytime sleep condition, consistent with data in workers on nightshift (Tilley et al., 1982). Overall KSS scores were ˚ kerstedt & in the low to moderate sleepiness range (A Gillberg, 1990). In contrast to the KSS, there were no main effects of condition on mood. However, participants in the split sleep condition reported lower mood and less positive affect across their work shift compared to the other conditions. This may have been due to baseline differences in mood ratings between the three groups. Given the link between circadian disruption and mood disturbance, close examination of the effects of split sleep schedules on mood should be considered in future studies. The findings of the current study are in line with previous studies examining different types of split sleep schedules (Mollicone et al., 2007, 2008). For example, Mollicone et al. (2007) described the effect on total sleep time of various combinations of nocturnal anchor sleep and diurnal nap. They found that sleep efficiency, performance on the PVT and subjective sleepiness were all found to be primarily a function of total time in bed regardless of how the sleep was divided between nocturnal anchor sleep and diurnal nap (Mollicone et al., 2007, 2008). The maintenance of performance observed in the split sleep condition in the current study may simply be due to the 10 h TIB in each 24 h sleep opportunity provided and the amount of sleep obtained by the participants, which was equivalent to the Chronobiology International

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

Efficacy of split sleep schedule on sleep and performance nighttime sleep condition. An equal division of the sleep opportunities, including a period of sleep placed at an adverse circadian phase, did not have a significant effect on performance, but may still be more beneficial for subjective sleepiness than consolidated daytime sleep, where individuals are awake for the whole night. The within-session results of the current study support this; sleepiness was relatively stable across the final daytime test bouts within each work day in the split sleep condition, whereas a dramatic increase in attentional lapses and KSS scores towards the end of the shift was observed in the daytime sleep condition. In the split sleep condition, part of the work period was conducted during the day (e.g. between 0900 h and 1400 h in the current study). This potentially reduced the performance impairment that can occur when the work period is placed at an adverse circadian time. The current study design for the split sleep group effectively reduced time awake/the length of the work period relative to the other conditions. Thus, a relative difference between the conditions may reflect the shortened wake opportunity in the split sleep condition. This raises the possibility of whether shift workers can get by with shorter sleep durations, so long as the intervening wake period is also short; thereby preventing the accumulation of homeostatic pressure and concomitant performance deterioration. Of further interest is the comparison of the two sleep opportunities in the split sleep condition. Participants in the split sleep condition obtained substantially more sleep during the morning sleep opportunity (0300 h– 0800 h) when sleep propensity was higher than during the afternoon/evening sleep opportunity (1500 h– 2000 h). This highlights the benefits of placing at least some of the available sleep opportunity during periods of high circadian sleep propensity. Both the duration and timing of rest opportunities play a role in determining the amount and quality of sleep that shift workers will obtain (Roach et al., 2003). Between shifts, night shift workers often have truncated diurnal sleep periods (Pilcher et al., 2000), presumably due to circadian drive for wakefulness occurring towards the end of the sleep period. With regards to work scheduling, there is a strong emphasis on number of work hours, shift length and types and speed of shift rotation, but, there is less focus on timing of rest opportunities. Scheduled rest breaks that do not take into account time of day influences on sleep may not allow shift workers sufficient sleep between shifts, regardless of the minimum break requirement and opportunity to recover. Overall, the findings of the current study have direct implications for rest break policy, for example, sleeper berth use in the trucking industry and rest breaks in aviation, mining and health care industries. Hours of service regulations could be adapted to allow for greater flexibility of the timing and duration of sleep, and also be more directed by the individual. Field studies of experienced nightshift workers have demonstrated that !

Informa Healthcare USA, Inc.

11

naps during the shift, although taken opportunistically, often occur during times when sleep propensity is high (Mollicone et al., 2008), suggesting that workers have a good understanding of when they can maximize their sleep opportunity. Further research is needed to investigate whether the results of the current study are replicable under real world circumstances, and the efficacy of different split sleep schedules. There are some limitations that should be noted. First, for participants in the nighttime consolidated sleep condition and the split sleep condition, the stay in laboratory ended on Day 10, while participants in the daytime sleep condition were from a longer 16-d study (Van Dongen et al., 2011). All groups knew how long they would be in the laboratory and knew their assigned sleep condition after the first baseline night. The prospect of additional time in the laboratory could have affected the participants in the daytime sleep condition, and perhaps this anticipation accounted for the changes observed. However, the findings with respect to total sleep time fit well with our knowledge of the effect of circadian rhythms on sleep propensity, thus making it less likely that they resulted from an anticipatory effect. Further, with the exception of differences in sleepiness (which were in accord with the differences in total sleep time), there were no differences among the conditions on the other subjective measures, one of which (the PANAS) included ratings of anxiety and another (the VAS-M) assessed depression. Thus, it seems reasonable to take the findings of the present study as a direct effect of the sleep condition manipulation (nighttime sleep, split sleep or daytime sleep) rather than any differences in the length of stay in the laboratory. The participants in this study were all young healthy males who were not shift workers. Given that it would be unlikely that shift workers in the real world would have 10-h opportunity for sleep on a regular basis, the results may be different in a chronically sleep restricted group. Similarly, in practice, a split schedule such as the one examined in the current study would require a second shift to work the opposite schedule (i.e. 0800 h–1500 h and 2000 h– 0300 h) so that 24-h coverage can be achieved. The practicality and efficacy of this alternate schedule requires further examination. Shiftwork is common in today’s society, and is associated with adverse health and safety outcomes as a result of poor sleep and impaired performance. It is important to examine alternative options for scheduling that may reduce this burden. Further research in shift work populations and in real-world situations is warranted to fully assess the efficacy of split sleep schedules.

ACKNOWLEDGEMENTS We thank the peer review committee of the project for their valuable comments and suggestions: Janet M.

12

M. L. Jackson et al.

Mullington, PhD, Goran Kecklund, PhD, and Nancy J. Wesensten, PhD (Chair). We thank Hans P.A. Van Dongen, PhD, for help with study design and for making available data and experimental materials of the study ‘‘Duration of Restart Period Needed to Recycle with Optimal Performance: Phase II’’ from which the data for the daytime sleep condition in this study were drawn. We also wish to thank the staff and students at Sleep and Performance Research Center, Washington State University, Spokane who assisted with data collection.

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

DECLARATION OF INTEREST This was not an industry supported study. Dr Belenky has received research funding from the Unites States Department of Transportation Federal Motor Carrier Safety Administration, Continental Airlines and United Airlines. The other authors have reported no conflicts of interest. This study was supported by the Federal Motor Carrier Safety Administration.

REFERENCES ˚ kerstedt T, Gillberg M. (1990). Subjective and objective sleepiness A in the active individual. Int J Neurosci. 52:29–37. ˚ kerstedt T. (2003). Shift work and disturbed sleep/wakefulness. A Occup Med. 53:89–94. Banks S, Van Dongen HPA, Maislin G, Dinges DF. (2010). Neurobehavioral dynamics following chronic sleep restriction: Dose-response effects of one night for recovery. Sleep. 33: 1013–26. Belenky G, Wesensten NJ, Thorne DR, et al. (2003). Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: A sleep dose-response study. J Sleep Res. 12:1–12. Belenky G, Hursh SR, Fitzpatrick J, Van Dongen HPA. (2008). Split sleeper berth use and driver performance: A review of the literature and application of a mathematical model predicting performance from sleep/wake history and circadian phase. Spokane, WA: Washington State University. Belenky G, Wu LJ, Jackson ML. (2011). Occupational sleep medicine. Practice and promise. In Van Dongen HPA, Kerkhof GA, eds. Progress in brain research. Oxford, UK: Elsevier BV, pp. 189–203. Bonnet MH, Arand DL. (2003). Clinical effects of sleep fragmentation versus sleep deprivation. Sleep Med Rev. 4:297–310. Bonnet MH. (1991). The effect of varying prophylactic naps on performance, alertness and mood throughout a 52-hour continuous operation. Sleep. 14:307–15. Dijk D-J, Czeisler CA. (1994). Paradoxical timing of the circadian rhythm of sleep propensity serves to consolidate sleep and wakefulness in humans. Neurosci Lett. 166:63–8. Dinges DF, Orne MT, Whitehouse WG, Orne EC. (1987). Temporal placement of a nap for alertness: Contributions of circadian phase and prior wakefulness. Sleep. 10:313–29. Dorrian J, Rogers NL, Dinges DF. (2005). Psychomotor vigilance performance: Neurocognitive assay sensitive to sleep loss. In Kushida C, ed. Sleep deprivation. Clinical issues, Pharmacology, and Sleep Loss Effects. New York: Marcel Dekker, pp. 39–70. Drake CL, Wright KP. (2011). Shift work, shift work disorder, and jet lag. In Kryger R, Dement W, eds. Principles and

practice of sleep medicine. 5th ed. St. Louis, MO: Elsevier, pp. 784–98. Eriksen CA, Gillberg M, Vestergren P. (2006). Sleepiness and sleep in a Simulated ‘‘Six Hours On/Six Hours Off’’ sea watch system. Chronobiol Int. 23:1193–202. Ficca G, Axelsson J, Mollicone DJ, et al. (2010). Naps, cognition and performance. Sleep Med Rev. 14:249–58. Folkard S, Tucker P. (2003). Shift work, safety and productivity. Occup Med. 53:95–101. Foret J, Benoit O. (1974). Sleep patterns of workers on rotating shifts. Electroencephalogr Clin Neurophysiol. 37:377–44. Goel N, Van Dongen HPA, Dinges DF. (2011). Circadian rhythms in sleepiness, alertness, and performance. In Kryger R, Dement W, eds. Principles and practice of sleep medicine. 5th ed. St. Louis, MO: Elsevier, pp. 445–55. Horne J, Reyner L. (1999). Vehicle accidents related to sleep: A review. Occup Environ Med. 56:289–94. Iber CS, Ancoli-Israel S. (2007). The AASM manual for the scoring of sleep and associated events: Rules, terminology and technical specifications. Westchester, IL: American Academy of Sleep Medicine. Jones C, Dorrian J, Jay S, et al. (2006). Self-awareness of impairment and the decision to drive after an extended period of wakefulness. Chronobiol Int. 23:1253–63. Lim J, Dinges DF. (2008). Sleep deprivation and vigilant attention. Ann NY Acad Sci. 1129:305–22. McDonald J, Potyk D, Fischer D, et al. (2013). Napping on the night shift: A naturalistic study of sleep, performance, and learning in physicians-in-training. J Grad Med Educ. 5:634–8. Mollicone DJ, Van Dongen HPA, Dinges DF. (2007). Optimizing sleep wake schedules in space: Sleep during chronic nocturnal sleep restriction with and without diurnal naps. Acta Astronaut. 60:354–61. Mollicone DJ, Van Dongen HPA, Rogers NL, Dinges DF. (2008). Response surface mapping of neurobehavioral performance: Testing the feasibility of split sleep schedules for space operations. Acta Astronaut. 63:833–40. Nicholson AN, Pascoe PA, Roehrs T, et al. (1985). Sustained performance with short evening and morning sleeps. Aviat Space Environ Med. 56:105–14. Paech GM, Ferguson SA, Sargent C, et al. (2012). The relative contributions of the homeostatic and circadian processes to sleep regulation under conditions of severe sleep restriction. Sleep 35:941–8. Pilcher JJ, Lambert BJ, Huffcutt AI. (2000). Differential effects of permanent and rotating shifts on self-report sleep length: A meta-analytic review. Sleep. 23:155–63. Portaluppi F, Smolensky MH, Touitou Y. (2010). Ethics and methods for biological rhythm research on animals and human beings. Chronobiol Int. 27:1911–29. Rajaratnam SM, Arendt J. (2001). Health in a 24-h society. Lancet. 358:999–1005. Roach GD, Reid KJ, Dawson D. (2003). The amount of sleep obtained by locomotive engineers: Effects of break duration and time of break onset. Occup Environ Med. 60:e17. doi:10.1136/ oem.60.12.e17. Sallinen M, Harma M, Akerstedt T, et al. (1998). Promoting alertness with a short nap during a night shift. J Sleep Res. 7:240–7. Santhi N, Horowitz TS, Duffy JF, Czeisler CA. (2007). Acute sleep deprivation and circadian misalignment associated with transition onto the first night of work impairs visual selective attention. PLoS One. 2:e1233. Schweitzer PK, Randazzo AC, Stone K, et al. (2006). Laboratory and field studies of naps and caffeine as practical countermeasures for sleep-wake problems associated with night work. Sleep. 29: 39–50. Takeyama H, Kubo T, Itani T. (2005). The nighttime nap strategies for improving night shift work in workplace. Ind Health. 43: 24–9. Chronobiology International

Efficacy of split sleep schedule on sleep and performance

Chronobiol Int Downloaded from informahealthcare.com by Dicle Univ. on 11/12/14 For personal use only.

Tilley AJ, Wilkinson RT, Warren PS, et al. (1982). The sleep and performance of shift workers. Hum Factors. 24:629–41. Van Dongen HPA, Maislin G, Mullington JM, Dinges DF. (2003). The cumulative cost of additional wakefulness: Dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep. 26: 117–26. Van Dongen HPA, Baynard M, Maislan G, Dinges D. (2004). Systematic interindividual differences in neurobehavioral impairment from sleep loss: Evidence of trait-like differential vulnerability. Sleep. 27:423–33. Van Dongen HPA, Jackson ML, Belenky G. (2010). Duration of restart period needed to recycle with optimal performance: Phase II. Technical Report No. FMCSA- RRR-10-062. Washington, DC: Federal Motor Carrier Safety Administration.

!

Informa Healthcare USA, Inc.

13

Van Dongen HPA, Belenky G, Vila BJ. (2011). The efficacy of a restart break for recycling with optimal performance depends critically on circadian timing. Sleep. 34:917–29. Watson D, Clark LA, Tellegen A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. J Personality Social Psychol. 54:1063–70. Wechsler D. (1997). WAIS-III administration and scoring manual. San Antonio, TX: The Psychological Corporation. Wehrens SMT, Hampton SM, Kerkhofs M, Skene DJ. (2012). Mood, alertness, and performance in response to sleep deprivation and recovery sleep in experienced shiftworkers versus nonshiftworkers. Chronobiol Int. 29:537–48. Wesensten NJ, Balkin T, Belenky G. (1999). Does sleep deprivation impact recuperation? A review and reanalysis. J Sleep Res. 8:237–45.

Investigation of the effectiveness of a split sleep schedule in sustaining sleep and maintaining performance.

Shift work is common in today's society, and is associated with negative health outcomes, and accidents and incidents. These detrimental effects can b...
701KB Sizes 1 Downloads 2 Views